Online 2d Arbitrary Sized Bin Packing Optimization Using 2pdc Heuristic: a Genetic Approach

This paper presents a Heuristic Genetic Algorithm (HGA) for optimizing two dimensional (2D) arbitrary sized heterogeneous box packing into a container, by considering practical constraints facing in the shipment container loading industries. Objective of this research is to pack heterogeneous boxes of varying length, width and constant height into a container of standard dimension, without violating major practical constraints to obtain a real time feasible packing pattern. The number of boxes will vary with time and the module accepts those boxes entered during processing which is commonly called as online packing. HGA is developed to maximize the container volume utilization and inturn profit. It significantly improves the search efficiency with less computational time and loads most of the heterogeneous boxes available at that time into the container by considering its optimal position and orientation. In general, HGA in comparison with the traditional genetic algorithm is substantially better and more satisfactory.